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focus on hospital1 and researcher
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‎projects/aries-fl/Dockerfile.ppmlcontroller

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FROM continuumio/miniconda3
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ENV WORKSPACE /workspace
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ARG jupyter_port
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ENV env_jupyter_port=jupyter_port
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# Setup workspace environment
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RUN apt-get update && apt-get install -y gcc
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# RUN conda install jupyter notebook=5.7.8
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RUN conda install jupyter notebook=6.1.5
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ADD projects/aries-fl/requirements.txt .
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#
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# .
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RUN pip install -r requirements.txt
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#RUN pip install aiohttp
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#RUN export PYTHONPATH="$PYTHONPATH:/aries_basic_controller"
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#ENV PYTHONPATH "${PYTHONPATH}:/aries_basic_controller"
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#RUN export JUPYTER_PATH="$JUPYTER_PATH:/aries_basic_controller"
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# Create jupyter notebook workspace
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#RUN mkdir $WORKSPACE
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WORKDIR $WORKSPACE
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# Make the image start the jupyer notebook
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COPY scripts/jupyter-entrypoint.sh /entrypoint.sh
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RUN chmod +x /entrypoint.sh
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# ENTRYPOINT ["/entrypoint.sh", "$env_jupyter_port"]
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ENTRYPOINT ["/entrypoint.sh", "8888"]

‎projects/aries-fl/docker-compose.yml

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researcher-notebook:
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build:
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context: ../../
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dockerfile: dockerfiles/controllers/Dockerfile.basiccontroller
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dockerfile: projects/aries-fl/Dockerfile.ppmlcontroller
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args:
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- jupyter_port=${RESEARCHER_JUPYTER_PORT}
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depends_on:
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hospital1-notebook:
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build:
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context: ../../
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dockerfile: dockerfiles/controllers/Dockerfile.basiccontroller
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dockerfile: projects/aries-fl/Dockerfile.ppmlcontroller
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args:
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- jupyter_port=${HOSPITAL1_JUPYTER_PORT}
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depends_on:
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hospital2-notebook:
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build:
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context: ../../
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dockerfile: dockerfiles/controllers/Dockerfile.basiccontroller
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dockerfile: projects/aries-fl/Dockerfile.ppmlcontroller
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args:
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- jupyter_port=${HOSPITAL2_JUPYTER_PORT}
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depends_on:
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hospital3-notebook:
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build:
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context: ../../
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dockerfile: dockerfiles/controllers/Dockerfile.basiccontroller
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dockerfile: projects/aries-fl/Dockerfile.ppmlcontroller
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args:
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- jupyter_port=${HOSPITAL3_JUPYTER_PORT}
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depends_on:

‎projects/aries-fl/manage

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# -----------------------------------------------------------------------------------------------------------------
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# Default Settings:
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# -----------------------------------------------------------------------------------------------------------------
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DEFAULT_CONTAINERS="nhstrust-agent nhstrust-notebook regulator-agent regulator-notebook researcher-agent researcher-notebook hospital1-agent hospital1-notebook hospital2-agent hospital2-notebook hospital3-agent hospital3-notebook"
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# DEFAULT_CONTAINERS="nhstrust-agent nhstrust-notebook regulator-agent regulator-notebook researcher-agent researcher-notebook hospital1-agent hospital1-notebook hospital2-agent hospital2-notebook hospital3-agent hospital3-notebook"
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DEFAULT_CONTAINERS="researcher-agent researcher-notebook hospital1-agent hospital1-notebook"
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# -----------------------------------------------------------------------------------------------------------------
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# Functions:
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# -----------------------------------------------------------------------------------------------------------------

‎projects/aries-fl/notebooks/Test/Test DP training.ipynb

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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"outputs": [
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{
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"ename": "ModuleNotFoundError",
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"evalue": "No module named 'torch'",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)",
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"\u001b[0;32m<ipython-input-1-ebded2444677>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mseaborn\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0msns\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 6\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0msys\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mtraceback\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'torch'"
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]
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}
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],
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"source": [
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"import numpy as np # linear algebra\n",
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"import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.12"
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"version": "3.8.5"
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}
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},
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"nbformat": 4,

‎projects/aries-fl/notebooks/hospital/Hospital.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "undefined-customs",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"IPython autoawait is `on`, and set to use `asyncio`\n"
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]
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}
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],
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"source": [
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"%autoawait\n",
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"import time\n",
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"import asyncio\n",
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"from aries_basic_controller.aries_controller import AriesAgentController\n",
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" \n",
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"WEBHOOK_HOST = \"0.0.0.0\"\n",
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"WEBHOOK_PORT = 8052\n",
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"WEBHOOK_BASE = \"\"\n",
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"ADMIN_URL = \"http://hospital1-agent:8051\"\n",
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"\n",
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"agent_controller = AriesAgentController(webhook_host=WEBHOOK_HOST, webhook_port=WEBHOOK_PORT,\n",
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" webhook_base=WEBHOOK_BASE, admin_url=ADMIN_URL)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "leading-madness",
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"metadata": {},
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"outputs": [],
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"source": [
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"\n",
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"loop = asyncio.get_event_loop()\n",
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"loop.create_task(agent_controller.listen_webhooks())\n",
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"\n",
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"def messages_handler(payload):\n",
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" connection_id = payload[\"connection_id\"]\n",
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" asyncio.get_event_loop().create_task(agent_controller.messaging.send_message(connection_id, \"This is a response from Bob\"))\n",
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" print(\"Handle message\", payload, connection_id)\n",
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"\n",
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"\n",
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"message_listener = {\n",
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" \"handler\": messages_handler,\n",
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" \"topic\": \"basicmessages\"\n",
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"}\n",
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"\n",
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"def connection_handler(payload):\n",
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" print(\"Connection Handler Called\")\n",
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" connection_id = payload[\"connection_id\"]\n",
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" state = payload[\"state\"]\n",
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" print(f\"Connection {connection_id} in State {state}\")\n",
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" \n",
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"connection_listener = {\n",
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" \"handler\": connection_handler,\n",
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" \"topic\": \"connections\"\n",
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"}\n",
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"\n",
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"agent_controller.register_listeners([connection_listener, message_listener], defaults=True)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "periodic-hepatitis",
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"metadata": {},
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"source": [
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"## Copy Invite from Researcher"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "right-guatemala",
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"metadata": {},
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"outputs": [],
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"source": [
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"#Paste in invitation from researcher agent\n",
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"invitation = {'@type': 'did:sov:BzCbsNYhMrjHiqZDTUASHg;spec/connections/1.0/invitation', '@id': '31d22c96-b531-467a-8637-867f0e9199ac', 'label': 'Health Researcher', 'serviceEndpoint': 'http://172.17.0.1:8040', 'recipientKeys': ['Hu8va1kwBxycxKa731q6FeenAmhk5s3x2X3MXXR7CckE']}"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "future-desert",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Connection Handler Called\n",
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"Connection ec35bfc5-68ef-45c4-87c6-5d9f63819c77 in State invitation\n",
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"Connection Handler Called\n",
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"Connection ec35bfc5-68ef-45c4-87c6-5d9f63819c77 in State request\n",
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"Connection {'invitation_key': 'Hu8va1kwBxycxKa731q6FeenAmhk5s3x2X3MXXR7CckE', 'state': 'request', 'connection_id': 'ec35bfc5-68ef-45c4-87c6-5d9f63819c77', 'routing_state': 'none', 'updated_at': '2021-01-23 14:22:15.871577Z', 'initiator': 'external', 'invitation_mode': 'once', 'created_at': '2021-01-23 14:22:15.851490Z', 'accept': 'manual', 'their_label': 'Health Researcher', 'my_did': 'ALrPXCqEuqa5wYFUDDkfeo', 'request_id': 'b9560178-dc00-4496-9a8c-2da146166b4d'}\n",
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"Connection Handler Called\n",
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"Connection ec35bfc5-68ef-45c4-87c6-5d9f63819c77 in State response\n",
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"Connection Handler Called\n",
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"Connection ec35bfc5-68ef-45c4-87c6-5d9f63819c77 in State active\n"
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]
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}
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],
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"source": [
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"# Receive Invitation\n",
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"response = await agent_controller.connections.accept_connection(invitation)\n",
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"# Print out accepted Invite and Alice's connection ID\n",
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"print(\"Connection\", response)\n",
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"alice_id = response[\"connection_id\"]\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "narrow-signature",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Print connection list\n",
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"connection = await agent_controller.connections.get_connection(alice_id)\n",
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"print(\"Alice AGENT CONNECTION\")\n",
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"print(connection)\n",
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"print(\"State:\", connection[\"state\"])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "bearing-tuition",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "encouraging-guard",
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"metadata": {},
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"outputs": [],
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"source": [
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"response = await agent_controller.terminate()\n",
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"print(response)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

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